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Cutoff of the Zarit Burden Interview in predicting depression and anxiety.
Yu, Yu; Liu, Zi-Wei; Zhou, Wei; Zhao, Mei; Qiu, Dan; Li, Yi-Lu; Xiao, Shui-Yuan.
Afiliação
  • Yu Y; Hospital Evaluation Office, Xiangya Hospital, Central South University, Xiangya Road 87, Changsha, 410008, Hunan, China.
  • Liu ZW; Department of Psychiatry, The Second Xiangya Hospital, Central South University, Renmin Middle Road 139, Changsha, 410011, Hunan, China.
  • Zhou W; Hospital Administration Institute, Xiangya Hospital, Central South University, Xiangya Road 87, Changsha, 410008, Hunan, China.
  • Zhao M; Department of Social Medicine and Health Management, Xiangya School of Public Health, Central South University, Upper Mayuanlin Road 238, Changsha, 410008, Hunan, China.
  • Qiu D; Department of Social Medicine and Health Management, Xiangya School of Public Health, Central South University, Upper Mayuanlin Road 238, Changsha, 410008, Hunan, China.
  • Li YL; Department of Social Medicine and Health Management, Xiangya School of Public Health, Central South University, Upper Mayuanlin Road 238, Changsha, 410008, Hunan, China.
  • Xiao SY; Mental Health Center, Xiangya Hospital, Central South University, Xiangya Road 87, Changsha, 410008, Hunan, China. xiaosy@csu.edu.cn.
Qual Life Res ; 28(9): 2525-2533, 2019 Sep.
Article em En | MEDLINE | ID: mdl-31089989
BACKGROUND: The purpose of the present study was to determine a statistically valid cutoff score for the Zarit Burden Interview (ZBI) in order to identify family caregivers at risk for depression and anxiety to guide for further assessment and future intervention. METHODS: The ZBI, the Patient Health Questionnaire (PHQ), and the Generalized Anxiety Disorder Scale (GAD) were administered to a representative community sample of 327 family caregivers of schizophrenia individuals. A ZBI cutoff score was determined using three different statistical methods: tree-based modeling, K-means clustering technique and linear regression, followed by contingency analysis and receiver operating characteristic (ROC) curve to compare between depression and anxiety scale scores with the ZBI cutoff. RESULTS: Findings suggest that a cutoff score of 48 in ZBI has significant predictive validity for identifying caregivers at risk for both depression and anxiety. A ZBI cutoff of 48 showed sensitivity of 73% for PHQ and 70% for GAD, specificity of 80% for PHQ and 79% for GAD, PPV (positive predictive value) of 75% for PHQ and 73% for GAD, NPV (negative predictive value) of 78% for PHQ and 76% for GAD. CONCLUSIONS: This cutoff score would enable health care providers to assess family caregivers at risk and provide necessary interventions to improve their quality of life in this important role.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Ansiedade / Psicometria / Qualidade de Vida / Cuidadores / Depressão Idioma: En Ano de publicação: 2019 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Ansiedade / Psicometria / Qualidade de Vida / Cuidadores / Depressão Idioma: En Ano de publicação: 2019 Tipo de documento: Article País de afiliação: China